NULL and NA are distinct. NULL means "not defined" and NA means "missing". The screenshot and the output of colSums() show that some NAs are present.
sum(is.na(your_data))
will return the total number in the data frame.
colSums(is.na(your_data))
gives the count of NA by column, and
rowSums(your_data)
shows the rows containing NA.
If
isn't working, we'd need to look at a representative data set. See the FAQ: How to do a minimal reproducible example reprex for beginners.